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Vision & Deep Learning Engineer

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Onsite

Vision & Deep Learning Engineer

Tonbo Imaging

Vision & Deep Learning Engineer

Skills

Deep LearningMachine Learning

3 years ago

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Important information


Contract type:

Permanent

Location:

Bengaluru, Karnataka, India

Work mode:

Onsite

Published on:

14 October 2026

What they need


Job highlights

  • The ideal candidate should be comfortable making significant contributions in a few of the following categories: * Developing creative computer vision and imaging software
  • Requirements: * BE / MS or PhD degree in Computer Science,Computer Vision,Machine Learning,or related technical field preferred. * 3+ years developing and designing Computer Vision technologies and systems

We are looking for an exceptional vision and deep-learning engineer with a proven track record in a computer vision and deep-learning (e.g. multiple view geometry, stereo imaging, object detection/tracking ). As an engineer, you will be solving challenges that are at the confluence of real-time vision.

Responsibilities
The ideal candidate should be comfortable making significant contributions in a few of the following categories:
* Developing creative computer vision and imaging software
* Developing novel real-time 3D scene reconstruction techniques and delivering accurate visual odometry systems.
* Applying machine learning to computer vision problems.
* Researching and prototyping techniques and algorithms for object detection and recognition.
* Developing robust software for integrating multiple sensors and tracking systems.
* Prototyping hardware and software solutions for tracking, detection and modeling.

Requirements:
* BE/MS or PhD degree in Computer Science, Computer Vision, Machine Learning, or related technical field preferred.
* 3+ years developing and designing Computer Vision technologies and systems
* 3+ years of experience engineering in C++
* Strong experince in implenting algorithms on CUDA
* Strong background in Computer Vision and Deep Learning
* Fast prototyping skills.
* Practical knowledge of machine learning, CNN, Bayesian filtering, information theory, and 3D geometry

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